440 search results - page 10 / 88 » A Fast Algorithm for Learning a Ranking Function from Large-... |
WWW
2008
ACM
14 years 8 months ago
2008
ACM
We consider the problem of ranking refinement, i.e., to improve the accuracy of an existing ranking function with a small set of labeled instances. We are, particularly, intereste...
ICMLA
2004
13 years 9 months ago
2004
AdaBoost rarely suffers from overfitting problems in low noise data cases. However, recent studies with highly noisy patterns clearly showed that overfitting can occur. A natural s...
IDA
2005
Springer
14 years 1 months ago
2005
Springer
We consider the problem of learning a ranking function, that is a mapping from instances to rankings over a finite number of labels. Our learning method, referred to as ranking by...
NIPS
2007
13 years 9 months ago
2007
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...